Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations30000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 MiB
Average record size in memory160.0 B

Variable types

Numeric19
Categorical1

Alerts

entropy_t is highly overall correlated with mean_f and 3 other fieldsHigh correlation
kurt_f is highly overall correlated with mean_f and 3 other fieldsHigh correlation
mean_f is highly overall correlated with entropy_t and 4 other fieldsHigh correlation
mean_t is highly overall correlated with med_t and 2 other fieldsHigh correlation
med_f is highly overall correlated with entropy_t and 6 other fieldsHigh correlation
med_t is highly overall correlated with mean_t and 2 other fieldsHigh correlation
min_f is highly overall correlated with entropy_t and 3 other fieldsHigh correlation
q75_t is highly overall correlated with entropy_tHigh correlation
sfm_f is highly overall correlated with kurt_f and 2 other fieldsHigh correlation
skew_f is highly overall correlated with kurt_f and 2 other fieldsHigh correlation
skew_t is highly overall correlated with mean_t and 2 other fieldsHigh correlation
std_f is highly overall correlated with mean_f and 2 other fieldsHigh correlation
std_t is highly overall correlated with mean_t and 2 other fieldsHigh correlation
q75_f is highly skewed (γ1 = -33.95199827)Skewed
q25_f has unique valuesUnique
q25_t has 27637 (92.1%) zerosZeros
q75_t has 1785 (5.9%) zerosZeros
skew_t has 17256 (57.5%) zerosZeros
zeroxrate_t has 18250 (60.8%) zerosZeros

Reproduction

Analysis started2024-10-10 12:46:24.719886
Analysis finished2024-10-10 12:47:27.401513
Duration1 minute and 2.68 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

mean_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.041594391
Minimum0.0024329233
Maximum0.20693557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:27.571032image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.0024329233
5-th percentile0.014664507
Q10.025799476
median0.03759306
Q30.053282735
95-th percentile0.081950992
Maximum0.20693557
Range0.20450265
Interquartile range (IQR)0.027483259

Descriptive statistics

Standard deviation0.02147506
Coefficient of variation (CV)0.51629701
Kurtosis2.0415555
Mean0.041594391
Median Absolute Deviation (MAD)0.013161733
Skewness1.1517884
Sum1247.8317
Variance0.00046117819
MonotonicityNot monotonic
2024-10-10T14:47:27.746203image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01691135933 2
 
< 0.1%
0.02156427536 2
 
< 0.1%
0.03049963923 2
 
< 0.1%
0.03000760193 1
 
< 0.1%
0.0285813327 1
 
< 0.1%
0.03956232988 1
 
< 0.1%
0.03477887123 1
 
< 0.1%
0.03787894531 1
 
< 0.1%
0.03304777659 1
 
< 0.1%
0.03877674893 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.002432923295 1
< 0.1%
0.002625390731 1
< 0.1%
0.002697979874 1
< 0.1%
0.002699792244 1
< 0.1%
0.002858414028 1
< 0.1%
0.003092089652 1
< 0.1%
0.003093305139 1
< 0.1%
0.003195140347 1
< 0.1%
0.003282912189 1
< 0.1%
0.003336638341 1
< 0.1%
ValueCountFrequency (%)
0.2069355717 1
< 0.1%
0.1866970078 1
< 0.1%
0.1822388175 1
< 0.1%
0.1776354677 1
< 0.1%
0.1729299883 1
< 0.1%
0.1693613906 1
< 0.1%
0.1667071437 1
< 0.1%
0.1656759904 1
< 0.1%
0.1641441945 1
< 0.1%
0.1619277681 1
< 0.1%

std_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08322155
Minimum0.019338027
Maximum0.21401169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:27.933715image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.019338027
5-th percentile0.045119144
Q10.063810621
median0.080169418
Q30.10022291
95-th percentile0.13128682
Maximum0.21401169
Range0.19467367
Interquartile range (IQR)0.036412293

Descriptive statistics

Standard deviation0.026389151
Coefficient of variation (CV)0.31709516
Kurtosis0.044266901
Mean0.08322155
Median Absolute Deviation (MAD)0.017886634
Skewness0.50649027
Sum2496.6465
Variance0.00069638727
MonotonicityNot monotonic
2024-10-10T14:47:28.121217image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05384132343 2
 
< 0.1%
0.06886790332 2
 
< 0.1%
0.07794866165 2
 
< 0.1%
0.0794194902 1
 
< 0.1%
0.07293853966 1
 
< 0.1%
0.07906831843 1
 
< 0.1%
0.07839262778 1
 
< 0.1%
0.07592022449 1
 
< 0.1%
0.07049620961 1
 
< 0.1%
0.08232523428 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.01933802729 1
< 0.1%
0.01950250913 1
< 0.1%
0.01993946155 1
< 0.1%
0.0202568184 1
< 0.1%
0.02097707606 1
< 0.1%
0.02114495775 1
< 0.1%
0.02123490749 1
< 0.1%
0.02137637206 1
< 0.1%
0.02147042685 1
< 0.1%
0.02153455085 1
< 0.1%
ValueCountFrequency (%)
0.214011693 1
< 0.1%
0.2046519085 1
< 0.1%
0.1986455854 1
< 0.1%
0.1941108283 1
< 0.1%
0.193553517 1
< 0.1%
0.193032361 1
< 0.1%
0.1899742919 1
< 0.1%
0.1875579522 1
< 0.1%
0.1873698188 1
< 0.1%
0.1860790309 1
< 0.1%

med_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.019323993
Minimum0.00094981735
Maximum0.16927095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:28.293119image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.00094981735
5-th percentile0.0058492445
Q10.010496631
median0.016145635
Q30.024826635
95-th percentile0.043786834
Maximum0.16927095
Range0.16832114
Interquartile range (IQR)0.014330004

Descriptive statistics

Standard deviation0.012446715
Coefficient of variation (CV)0.64410678
Kurtosis5.1715472
Mean0.019323993
Median Absolute Deviation (MAD)0.0065856912
Skewness1.7424629
Sum579.71978
Variance0.00015492071
MonotonicityNot monotonic
2024-10-10T14:47:28.470865image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.006540780801 2
 
< 0.1%
0.009887705598 2
 
< 0.1%
0.01344689357 2
 
< 0.1%
0.01381421652 1
 
< 0.1%
0.0123951615 1
 
< 0.1%
0.02195596241 1
 
< 0.1%
0.01823237173 1
 
< 0.1%
0.02118277834 1
 
< 0.1%
0.01759132278 1
 
< 0.1%
0.02010214708 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.0009498173517 1
< 0.1%
0.0009710029518 1
< 0.1%
0.001041600911 1
< 0.1%
0.001113147757 1
< 0.1%
0.001136185481 1
< 0.1%
0.001143363949 1
< 0.1%
0.001178038626 1
< 0.1%
0.001186052344 1
< 0.1%
0.001193763431 1
< 0.1%
0.001198232493 1
< 0.1%
ValueCountFrequency (%)
0.1692709529 1
< 0.1%
0.1426382144 1
< 0.1%
0.1222340397 1
< 0.1%
0.1149326616 1
< 0.1%
0.1141005385 1
< 0.1%
0.1105491309 1
< 0.1%
0.1036250669 1
< 0.1%
0.1031499609 1
< 0.1%
0.1020907493 1
< 0.1%
0.1015391795 1
< 0.1%

min_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0063271435
Minimum0.000457067
Maximum0.068671371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:28.642742image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.000457067
5-th percentile0.0023912449
Q10.0039290739
median0.0055798086
Q30.0079141598
95-th percentile0.01276109
Maximum0.068671371
Range0.068214304
Interquartile range (IQR)0.0039850859

Descriptive statistics

Standard deviation0.0033698602
Coefficient of variation (CV)0.53260373
Kurtosis6.9034881
Mean0.0063271435
Median Absolute Deviation (MAD)0.0019016093
Skewness1.6085515
Sum189.81431
Variance1.1355958 × 10-5
MonotonicityNot monotonic
2024-10-10T14:47:29.005847image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.003062977506 2
 
< 0.1%
0.003953284292 2
 
< 0.1%
0.005407428943 2
 
< 0.1%
0.005128016388 1
 
< 0.1%
0.005436888398 1
 
< 0.1%
0.004762191307 1
 
< 0.1%
0.004974793015 1
 
< 0.1%
0.005372201567 1
 
< 0.1%
0.004098571969 1
 
< 0.1%
0.008092636721 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.000457067 1
< 0.1%
0.0004850969617 1
< 0.1%
0.0005224592533 1
< 0.1%
0.0005353357765 1
< 0.1%
0.0005666385006 1
< 0.1%
0.0006006549532 1
< 0.1%
0.0006165422118 1
< 0.1%
0.0006253345607 1
< 0.1%
0.0006389036751 1
< 0.1%
0.000642165194 1
< 0.1%
ValueCountFrequency (%)
0.0686713712 1
< 0.1%
0.03275590678 1
< 0.1%
0.03232972684 1
< 0.1%
0.03116207365 1
< 0.1%
0.0304447999 1
< 0.1%
0.0302638373 1
< 0.1%
0.02836160781 1
< 0.1%
0.02815050023 1
< 0.1%
0.02599723445 1
< 0.1%
0.02590508764 1
< 0.1%

q25_f
Real number (ℝ)

UNIQUE 

Distinct30000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.36591292
Minimum0.12191156
Maximum0.94680114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:29.184300image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.12191156
5-th percentile0.22879663
Q10.3085663
median0.36673757
Q30.42311093
95-th percentile0.49900003
Maximum0.94680114
Range0.82488958
Interquartile range (IQR)0.11454463

Descriptive statistics

Standard deviation0.082126946
Coefficient of variation (CV)0.22444396
Kurtosis-0.23278915
Mean0.36591292
Median Absolute Deviation (MAD)0.057172486
Skewness-0.0018582855
Sum10977.388
Variance0.0067448352
MonotonicityNot monotonic
2024-10-10T14:47:29.356167image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4369868916 1
 
< 0.1%
0.32223895 1
 
< 0.1%
0.4749433398 1
 
< 0.1%
0.3899784348 1
 
< 0.1%
0.3954654175 1
 
< 0.1%
0.4015442173 1
 
< 0.1%
0.3919608311 1
 
< 0.1%
0.3360451842 1
 
< 0.1%
0.4511630338 1
 
< 0.1%
0.3602061153 1
 
< 0.1%
Other values (29990) 29990
> 99.9%
ValueCountFrequency (%)
0.1219115619 1
< 0.1%
0.1226686769 1
< 0.1%
0.123836379 1
< 0.1%
0.1254518063 1
< 0.1%
0.1265465485 1
< 0.1%
0.1270145248 1
< 0.1%
0.1271995574 1
< 0.1%
0.1272845797 1
< 0.1%
0.1277742624 1
< 0.1%
0.1297505695 1
< 0.1%
ValueCountFrequency (%)
0.9468011424 1
< 0.1%
0.6850490588 1
< 0.1%
0.6607256613 1
< 0.1%
0.6420695273 1
< 0.1%
0.6318320579 1
< 0.1%
0.6309941062 1
< 0.1%
0.6301948853 1
< 0.1%
0.6296651125 1
< 0.1%
0.629414305 1
< 0.1%
0.6267332787 1
< 0.1%

q75_f
Real number (ℝ)

SKEWED 

Distinct64
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.99971069
Minimum0.49133568
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:29.512609image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.49133568
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0.50866432
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0078205736
Coefficient of variation (CV)0.0078228368
Kurtosis1383.5134
Mean0.99971069
Median Absolute Deviation (MAD)0
Skewness-33.951998
Sum29991.321
Variance6.1161371 × 10-5
MonotonicityNot monotonic
2024-10-10T14:47:29.699900image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 29937
99.8%
0.9958632649 1
 
< 0.1%
0.8427068512 1
 
< 0.1%
0.997407896 1
 
< 0.1%
0.8001825676 1
 
< 0.1%
0.6764609391 1
 
< 0.1%
0.4913356789 1
 
< 0.1%
0.7720953544 1
 
< 0.1%
0.7771386736 1
 
< 0.1%
0.9636803538 1
 
< 0.1%
Other values (54) 54
 
0.2%
ValueCountFrequency (%)
0.4913356789 1
< 0.1%
0.6384324327 1
< 0.1%
0.6764609391 1
< 0.1%
0.7197812187 1
< 0.1%
0.7216111445 1
< 0.1%
0.732653098 1
< 0.1%
0.73307925 1
< 0.1%
0.7405699139 1
< 0.1%
0.7574959024 1
< 0.1%
0.7630778123 1
< 0.1%
ValueCountFrequency (%)
1 29937
99.8%
0.9991934605 1
 
< 0.1%
0.997407896 1
 
< 0.1%
0.9958632649 1
 
< 0.1%
0.9879303407 1
 
< 0.1%
0.9878227338 1
 
< 0.1%
0.984210948 1
 
< 0.1%
0.980603152 1
 
< 0.1%
0.9804979372 1
 
< 0.1%
0.9788610498 1
 
< 0.1%

skew_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3300588
Minimum0.10724644
Maximum0.61376755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:29.871527image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.10724644
5-th percentile0.20743523
Q10.27232345
median0.32376248
Q30.38509507
95-th percentile0.46895088
Maximum0.61376755
Range0.50652111
Interquartile range (IQR)0.11277162

Descriptive statistics

Standard deviation0.079558826
Coefficient of variation (CV)0.2410444
Kurtosis-0.38670987
Mean0.3300588
Median Absolute Deviation (MAD)0.055901663
Skewness0.25363626
Sum9901.7641
Variance0.0063296068
MonotonicityNot monotonic
2024-10-10T14:47:30.043392image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4417016574 2
 
< 0.1%
0.3859123538 2
 
< 0.1%
0.3671032355 2
 
< 0.1%
0.3509743446 1
 
< 0.1%
0.4098905111 1
 
< 0.1%
0.2097932843 1
 
< 0.1%
0.2571053754 1
 
< 0.1%
0.2497816288 1
 
< 0.1%
0.228971273 1
 
< 0.1%
0.3878191063 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.1072464379 1
< 0.1%
0.1116372129 1
< 0.1%
0.1146578384 1
< 0.1%
0.1178989284 1
< 0.1%
0.1222194468 1
< 0.1%
0.1265406274 1
< 0.1%
0.1278781967 1
< 0.1%
0.1278830807 1
< 0.1%
0.1289655993 1
< 0.1%
0.1300871425 1
< 0.1%
ValueCountFrequency (%)
0.6137675492 1
< 0.1%
0.6119739963 1
< 0.1%
0.6048312994 1
< 0.1%
0.5988718243 1
< 0.1%
0.5941168962 1
< 0.1%
0.5937750385 1
< 0.1%
0.593344554 1
< 0.1%
0.5918717557 1
< 0.1%
0.5879529118 1
< 0.1%
0.5863845051 1
< 0.1%

kurt_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29781
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.38569424
Minimum0.10891136
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:30.230702image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.10891136
5-th percentile0.22055911
Q10.29785633
median0.36459788
Q30.44675533
95-th percentile0.61200083
Maximum1
Range0.89108864
Interquartile range (IQR)0.148899

Descriptive statistics

Standard deviation0.13053625
Coefficient of variation (CV)0.33844492
Kurtosis4.1862851
Mean0.38569424
Median Absolute Deviation (MAD)0.073186518
Skewness1.5231437
Sum11570.827
Variance0.017039714
MonotonicityNot monotonic
2024-10-10T14:47:30.402593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 217
 
0.7%
0.4540222185 2
 
< 0.1%
0.5745258772 2
 
< 0.1%
0.4049866206 2
 
< 0.1%
0.3776731391 1
 
< 0.1%
0.4254510001 1
 
< 0.1%
0.2322589184 1
 
< 0.1%
0.2685600497 1
 
< 0.1%
0.2226294596 1
 
< 0.1%
0.2081901693 1
 
< 0.1%
Other values (29771) 29771
99.2%
ValueCountFrequency (%)
0.1089113582 1
< 0.1%
0.1185724959 1
< 0.1%
0.1206416042 1
< 0.1%
0.1239412007 1
< 0.1%
0.125524456 1
< 0.1%
0.1312072118 1
< 0.1%
0.1317956914 1
< 0.1%
0.1327922282 1
< 0.1%
0.1362090174 1
< 0.1%
0.1367268461 1
< 0.1%
ValueCountFrequency (%)
1 217
0.7%
0.9994480779 1
 
< 0.1%
0.9980957882 1
 
< 0.1%
0.9973495328 1
 
< 0.1%
0.9968274687 1
 
< 0.1%
0.9938188533 1
 
< 0.1%
0.9921344242 1
 
< 0.1%
0.9918432346 1
 
< 0.1%
0.9904255775 1
 
< 0.1%
0.9871955592 1
 
< 0.1%

sfm_f
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.32566137
Minimum0.10691048
Maximum0.60957184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:30.564379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.10691048
5-th percentile0.20551477
Q10.26864951
median0.3195536
Q30.37938568
95-th percentile0.46256338
Maximum0.60957184
Range0.50266136
Interquartile range (IQR)0.11073616

Descriptive statistics

Standard deviation0.078222634
Coefficient of variation (CV)0.24019623
Kurtosis-0.38655182
Mean0.32566137
Median Absolute Deviation (MAD)0.05487133
Skewness0.2597048
Sum9769.841
Variance0.0061187805
MonotonicityNot monotonic
2024-10-10T14:47:30.758115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4312840335 2
 
< 0.1%
0.379117999 2
 
< 0.1%
0.3624380604 2
 
< 0.1%
0.3473179532 1
 
< 0.1%
0.4081865049 1
 
< 0.1%
0.2090661651 1
 
< 0.1%
0.2557332607 1
 
< 0.1%
0.2490349694 1
 
< 0.1%
0.2276768715 1
 
< 0.1%
0.3858252428 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.1069104808 1
< 0.1%
0.1103117146 1
< 0.1%
0.1137757006 1
< 0.1%
0.117738918 1
< 0.1%
0.1219025879 1
< 0.1%
0.1247267765 1
< 0.1%
0.1260044725 1
< 0.1%
0.126701351 1
< 0.1%
0.1268336322 1
< 0.1%
0.1271324033 1
< 0.1%
ValueCountFrequency (%)
0.609571841 1
< 0.1%
0.6065222483 1
< 0.1%
0.6010492789 1
< 0.1%
0.5929245016 1
< 0.1%
0.5909491622 1
< 0.1%
0.5897739686 1
< 0.1%
0.5884963338 1
< 0.1%
0.5875188936 1
< 0.1%
0.5872976464 1
< 0.1%
0.5837396805 1
< 0.1%

cent_f
Real number (ℝ)

Distinct1182
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.99684446
Minimum0.62527722
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:30.930003image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.62527722
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0.37472278
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.020010489
Coefficient of variation (CV)0.020073832
Kurtosis77.991518
Mean0.99684446
Median Absolute Deviation (MAD)0
Skewness-8.1429131
Sum29905.334
Variance0.00040041965
MonotonicityNot monotonic
2024-10-10T14:47:31.102118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 28819
96.1%
0.9020319469 1
 
< 0.1%
0.8700139061 1
 
< 0.1%
0.9239953231 1
 
< 0.1%
0.9253693404 1
 
< 0.1%
0.8610432202 1
 
< 0.1%
0.9833726682 1
 
< 0.1%
0.913478811 1
 
< 0.1%
0.9973518009 1
 
< 0.1%
0.9892329949 1
 
< 0.1%
Other values (1172) 1172
 
3.9%
ValueCountFrequency (%)
0.6252772169 1
< 0.1%
0.6589549561 1
< 0.1%
0.6751562135 1
< 0.1%
0.6810257491 1
< 0.1%
0.6917380231 1
< 0.1%
0.6935746483 1
< 0.1%
0.6981034213 1
< 0.1%
0.7033796022 1
< 0.1%
0.704534597 1
< 0.1%
0.7051810715 1
< 0.1%
ValueCountFrequency (%)
1 28819
96.1%
0.9999468329 1
 
< 0.1%
0.9998654135 1
 
< 0.1%
0.9995716957 1
 
< 0.1%
0.9994990916 1
 
< 0.1%
0.9994929571 1
 
< 0.1%
0.9994236925 1
 
< 0.1%
0.9994121549 1
 
< 0.1%
0.9993825819 1
 
< 0.1%
0.9993538126 1
 
< 0.1%

mean_t
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49253919
Minimum0.26525074
Maximum0.75243299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:31.445625image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.26525074
5-th percentile0.40036193
Q10.45220859
median0.49143002
Q30.53092328
95-th percentile0.58991711
Maximum0.75243299
Range0.48718225
Interquartile range (IQR)0.078714697

Descriptive statistics

Standard deviation0.058166736
Coefficient of variation (CV)0.11809565
Kurtosis0.1914887
Mean0.49253919
Median Absolute Deviation (MAD)0.039366772
Skewness0.16376152
Sum14776.176
Variance0.0033833692
MonotonicityNot monotonic
2024-10-10T14:47:31.622241image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5704646327 2
 
< 0.1%
0.5076350555 2
 
< 0.1%
0.5755580831 2
 
< 0.1%
0.5475404033 1
 
< 0.1%
0.5158039141 1
 
< 0.1%
0.4726256763 1
 
< 0.1%
0.5018732276 1
 
< 0.1%
0.4606208093 1
 
< 0.1%
0.4657838766 1
 
< 0.1%
0.5515422065 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.2652507415 1
< 0.1%
0.2798342496 1
< 0.1%
0.2810117111 1
< 0.1%
0.2906600677 1
< 0.1%
0.29413338 1
< 0.1%
0.2949584452 1
< 0.1%
0.295610358 1
< 0.1%
0.3007679486 1
< 0.1%
0.3011998359 1
< 0.1%
0.301222476 1
< 0.1%
ValueCountFrequency (%)
0.7524329893 1
< 0.1%
0.7388335927 1
< 0.1%
0.7306876618 1
< 0.1%
0.7293301986 1
< 0.1%
0.722926669 1
< 0.1%
0.7221573176 1
< 0.1%
0.7190348154 1
< 0.1%
0.716931531 1
< 0.1%
0.7166992886 1
< 0.1%
0.7160976496 1
< 0.1%

std_t
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57643057
Minimum0.32606066
Maximum0.83761364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:31.800771image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.32606066
5-th percentile0.4727404
Q10.53271271
median0.57545324
Q30.61859448
95-th percentile0.68436906
Maximum0.83761364
Range0.51155298
Interquartile range (IQR)0.085881763

Descriptive statistics

Standard deviation0.064684868
Coefficient of variation (CV)0.11221623
Kurtosis0.18515367
Mean0.57643057
Median Absolute Deviation (MAD)0.042940799
Skewness0.10219101
Sum17292.917
Variance0.0041841322
MonotonicityNot monotonic
2024-10-10T14:47:31.963872image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6807491816 2
 
< 0.1%
0.607332422 2
 
< 0.1%
0.6687650386 2
 
< 0.1%
0.6436227505 1
 
< 0.1%
0.5926042567 1
 
< 0.1%
0.5662093179 1
 
< 0.1%
0.5963955422 1
 
< 0.1%
0.5366004438 1
 
< 0.1%
0.5610639573 1
 
< 0.1%
0.6136940013 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.3260606605 1
< 0.1%
0.3312200205 1
< 0.1%
0.3355419065 1
< 0.1%
0.3376674155 1
< 0.1%
0.3442055965 1
< 0.1%
0.3461962673 1
< 0.1%
0.3482751757 1
< 0.1%
0.3484815626 1
< 0.1%
0.3557000935 1
< 0.1%
0.3564560118 1
< 0.1%
ValueCountFrequency (%)
0.8376136377 1
< 0.1%
0.83401374 1
< 0.1%
0.8162561884 1
< 0.1%
0.8131432451 1
< 0.1%
0.8122573808 1
< 0.1%
0.8089709759 1
< 0.1%
0.8062015605 1
< 0.1%
0.8061078401 1
< 0.1%
0.8044782449 1
< 0.1%
0.8016364367 1
< 0.1%

med_t
Real number (ℝ)

HIGH CORRELATION 

Distinct29997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49290541
Minimum0.26772551
Maximum0.75377955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:32.135549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.26772551
5-th percentile0.40082134
Q10.45251176
median0.49173369
Q30.53131948
95-th percentile0.59039955
Maximum0.75377955
Range0.48605404
Interquartile range (IQR)0.078807728

Descriptive statistics

Standard deviation0.058190622
Coefficient of variation (CV)0.11805637
Kurtosis0.19085269
Mean0.49290541
Median Absolute Deviation (MAD)0.03940559
Skewness0.16435353
Sum14787.162
Variance0.0033861484
MonotonicityNot monotonic
2024-10-10T14:47:32.323244image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5709176079 2
 
< 0.1%
0.5080711147 2
 
< 0.1%
0.5759368315 2
 
< 0.1%
0.5479553376 1
 
< 0.1%
0.5158085116 1
 
< 0.1%
0.472748667 1
 
< 0.1%
0.5021756799 1
 
< 0.1%
0.4606956452 1
 
< 0.1%
0.465916252 1
 
< 0.1%
0.551648886 1
 
< 0.1%
Other values (29987) 29987
> 99.9%
ValueCountFrequency (%)
0.2677255098 1
< 0.1%
0.2801089709 1
< 0.1%
0.2810786404 1
< 0.1%
0.2908797976 1
< 0.1%
0.2944433464 1
< 0.1%
0.2954340121 1
< 0.1%
0.2958489416 1
< 0.1%
0.3013218699 1
< 0.1%
0.3013887321 1
< 0.1%
0.3014487637 1
< 0.1%
ValueCountFrequency (%)
0.7537795525 1
< 0.1%
0.7394161937 1
< 0.1%
0.7308380928 1
< 0.1%
0.7293796156 1
< 0.1%
0.72301004 1
< 0.1%
0.7222626534 1
< 0.1%
0.7190730061 1
< 0.1%
0.7172800219 1
< 0.1%
0.7169990713 1
< 0.1%
0.7169262828 1
< 0.1%

q25_t
Real number (ℝ)

ZEROS 

Distinct2364
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0041440121
Minimum0
Maximum0.18737198
Zeros27637
Zeros (%)92.1%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:32.494922image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.033637253
Maximum0.18737198
Range0.18737198
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.017574911
Coefficient of variation (CV)4.2410376
Kurtosis28.42836
Mean0.0041440121
Median Absolute Deviation (MAD)0
Skewness5.0932774
Sum124.32036
Variance0.00030887751
MonotonicityNot monotonic
2024-10-10T14:47:32.666794image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27637
92.1%
0.01051914931 1
 
< 0.1%
0.09102646052 1
 
< 0.1%
0.01429169867 1
 
< 0.1%
0.1008503391 1
 
< 0.1%
0.03682817515 1
 
< 0.1%
0.04675957116 1
 
< 0.1%
0.03997470655 1
 
< 0.1%
0.1042435425 1
 
< 0.1%
0.07774241744 1
 
< 0.1%
Other values (2354) 2354
 
7.8%
ValueCountFrequency (%)
0 27637
92.1%
3.274887597 × 10-51
 
< 0.1%
7.944908128 × 10-51
 
< 0.1%
8.447656715 × 10-51
 
< 0.1%
0.0001095215388 1
 
< 0.1%
0.0001416360554 1
 
< 0.1%
0.0001747908201 1
 
< 0.1%
0.0002342783705 1
 
< 0.1%
0.0002677712451 1
 
< 0.1%
0.0002818661139 1
 
< 0.1%
ValueCountFrequency (%)
0.1873719807 1
< 0.1%
0.182711939 1
< 0.1%
0.1804346023 1
< 0.1%
0.1761896615 1
< 0.1%
0.1752928744 1
< 0.1%
0.1725185021 1
< 0.1%
0.1724996663 1
< 0.1%
0.1724451227 1
< 0.1%
0.1686847939 1
< 0.1%
0.1683049302 1
< 0.1%

q75_t
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16538
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60344724
Minimum0
Maximum1
Zeros1785
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:32.849637image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.21858924
median0.66284286
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.78141076

Descriptive statistics

Standard deviation0.38747038
Coefficient of variation (CV)0.64209487
Kurtosis-1.5738446
Mean0.60344724
Median Absolute Deviation (MAD)0.33715714
Skewness-0.26664576
Sum18103.417
Variance0.15013329
MonotonicityNot monotonic
2024-10-10T14:47:33.037158image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 11679
38.9%
0 1785
 
5.9%
0.03169437382 1
 
< 0.1%
0.007202374753 1
 
< 0.1%
0.213519626 1
 
< 0.1%
0.09590718441 1
 
< 0.1%
0.01989077995 1
 
< 0.1%
0.01173467994 1
 
< 0.1%
0.1436540825 1
 
< 0.1%
0.09599410254 1
 
< 0.1%
Other values (16528) 16528
55.1%
ValueCountFrequency (%)
0 1785
5.9%
9.004768566 × 10-61
 
< 0.1%
3.274887597 × 10-51
 
< 0.1%
4.588437537 × 10-51
 
< 0.1%
7.387674221 × 10-51
 
< 0.1%
7.944908128 × 10-51
 
< 0.1%
0.000129382415 1
 
< 0.1%
0.0001780336849 1
 
< 0.1%
0.0002216709115 1
 
< 0.1%
0.0002311236476 1
 
< 0.1%
ValueCountFrequency (%)
1 11679
38.9%
0.9999177048 1
 
< 0.1%
0.9998223625 1
 
< 0.1%
0.9996442578 1
 
< 0.1%
0.9996441574 1
 
< 0.1%
0.9996097042 1
 
< 0.1%
0.9995512034 1
 
< 0.1%
0.9994477625 1
 
< 0.1%
0.999038308 1
 
< 0.1%
0.9990200805 1
 
< 0.1%

skew_t
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12745
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.021828744
Minimum0
Maximum0.37819433
Zeros17256
Zeros (%)57.5%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:33.211107image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.034751488
95-th percentile0.09863416
Maximum0.37819433
Range0.37819433
Interquartile range (IQR)0.034751488

Descriptive statistics

Standard deviation0.036997412
Coefficient of variation (CV)1.6948942
Kurtosis7.5913733
Mean0.021828744
Median Absolute Deviation (MAD)0
Skewness2.3321735
Sum654.86232
Variance0.0013688085
MonotonicityNot monotonic
2024-10-10T14:47:33.391424image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17256
57.5%
0.08904221652 1
 
< 0.1%
0.08135776456 1
 
< 0.1%
0.07359106804 1
 
< 0.1%
0.1162173221 1
 
< 0.1%
0.07715453561 1
 
< 0.1%
0.03686009036 1
 
< 0.1%
0.09539903708 1
 
< 0.1%
0.1051100625 1
 
< 0.1%
0.06272221614 1
 
< 0.1%
Other values (12735) 12735
42.4%
ValueCountFrequency (%)
0 17256
57.5%
1.838501163 × 10-61
 
< 0.1%
3.980021934 × 10-61
 
< 0.1%
7.809031105 × 10-61
 
< 0.1%
1.222086524 × 10-51
 
< 0.1%
3.156242966 × 10-51
 
< 0.1%
3.969175298 × 10-51
 
< 0.1%
4.268361527 × 10-51
 
< 0.1%
4.316898559 × 10-51
 
< 0.1%
4.637145292 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.3781943298 1
< 0.1%
0.3668659577 1
< 0.1%
0.3594696567 1
< 0.1%
0.3380707717 1
< 0.1%
0.3353084094 1
< 0.1%
0.3336702084 1
< 0.1%
0.3308460836 1
< 0.1%
0.3262885839 1
< 0.1%
0.3235967575 1
< 0.1%
0.3207642786 1
< 0.1%

kurt_t
Real number (ℝ)

Distinct322
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.99500006
Minimum0
Maximum1
Zeros23
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:33.563316image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.057327433
Coefficient of variation (CV)0.057615507
Kurtosis193.13634
Mean0.99500006
Median Absolute Deviation (MAD)0
Skewness-13.400726
Sum29850.002
Variance0.0032864346
MonotonicityNot monotonic
2024-10-10T14:47:33.750847image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 29657
98.9%
0 23
 
0.1%
0.4334816733 1
 
< 0.1%
0.5724249488 1
 
< 0.1%
0.7355173022 1
 
< 0.1%
0.2229556742 1
 
< 0.1%
0.1885428404 1
 
< 0.1%
0.4225154771 1
 
< 0.1%
0.3898323463 1
 
< 0.1%
0.1784495931 1
 
< 0.1%
Other values (312) 312
 
1.0%
ValueCountFrequency (%)
0 23
0.1%
0.0007529271883 1
 
< 0.1%
0.004330211519 1
 
< 0.1%
0.005186609484 1
 
< 0.1%
0.006340507792 1
 
< 0.1%
0.01933843149 1
 
< 0.1%
0.02412515772 1
 
< 0.1%
0.03255489696 1
 
< 0.1%
0.04160044546 1
 
< 0.1%
0.0428988548 1
 
< 0.1%
ValueCountFrequency (%)
1 29657
98.9%
0.9985670905 1
 
< 0.1%
0.9961808973 1
 
< 0.1%
0.9946361868 1
 
< 0.1%
0.9935805091 1
 
< 0.1%
0.9933177553 1
 
< 0.1%
0.9931397698 1
 
< 0.1%
0.992981608 1
 
< 0.1%
0.9894023792 1
 
< 0.1%
0.9870325169 1
 
< 0.1%

zeroxrate_t
Real number (ℝ)

ZEROS 

Distinct5884
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0069000474
Minimum0
Maximum0.25439453
Zeros18250
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:34.085932image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0053710938
95-th percentile0.038085938
Maximum0.25439453
Range0.25439453
Interquartile range (IQR)0.0053710938

Descriptive statistics

Standard deviation0.016993682
Coefficient of variation (CV)2.4628355
Kurtosis25.915494
Mean0.0069000474
Median Absolute Deviation (MAD)0
Skewness4.3527196
Sum207.00142
Variance0.00028878522
MonotonicityNot monotonic
2024-10-10T14:47:34.273229image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18250
60.8%
0.00048828125 359
 
1.2%
0.0009765625 228
 
0.8%
0.00244140625 204
 
0.7%
0.00146484375 187
 
0.6%
0.001953125 183
 
0.6%
0.0029296875 178
 
0.6%
0.00390625 170
 
0.6%
0.00341796875 157
 
0.5%
0.0048828125 146
 
0.5%
Other values (5874) 9938
33.1%
ValueCountFrequency (%)
0 18250
60.8%
0.0002492092646 1
 
< 0.1%
0.000253499771 1
 
< 0.1%
0.0002819280909 1
 
< 0.1%
0.0002858738309 1
 
< 0.1%
0.0002863051184 1
 
< 0.1%
0.0002881295874 1
 
< 0.1%
0.0002973399191 1
 
< 0.1%
0.0002991988711 1
 
< 0.1%
0.0003031269102 1
 
< 0.1%
ValueCountFrequency (%)
0.2543945312 1
< 0.1%
0.2446289062 1
< 0.1%
0.220328128 1
< 0.1%
0.2065429688 1
< 0.1%
0.1948242188 1
< 0.1%
0.1870117188 1
< 0.1%
0.1838682247 1
< 0.1%
0.1824554066 1
< 0.1%
0.181640625 1
< 0.1%
0.1801757812 1
< 0.1%

entropy_t
Real number (ℝ)

HIGH CORRELATION 

Distinct17494
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86879036
Minimum0.054824435
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-10-10T14:47:34.429512image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0.054824435
5-th percentile0.51217492
Q10.7767301
median0.94649756
Q31
95-th percentile1
Maximum1
Range0.94517557
Interquartile range (IQR)0.2232699

Descriptive statistics

Standard deviation0.16789411
Coefficient of variation (CV)0.19325042
Kurtosis0.98478992
Mean0.86879036
Median Absolute Deviation (MAD)0.053502444
Skewness-1.3109434
Sum26063.711
Variance0.028188431
MonotonicityNot monotonic
2024-10-10T14:47:34.622309image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 12506
41.7%
0.968774242 2
 
< 0.1%
0.6514403255 1
 
< 0.1%
0.8454661702 1
 
< 0.1%
0.6127226688 1
 
< 0.1%
0.888770803 1
 
< 0.1%
0.7043260873 1
 
< 0.1%
0.9359590913 1
 
< 0.1%
0.7619587291 1
 
< 0.1%
0.8594213927 1
 
< 0.1%
Other values (17484) 17484
58.3%
ValueCountFrequency (%)
0.05482443478 1
< 0.1%
0.1841074425 1
< 0.1%
0.2234874843 1
< 0.1%
0.2284804879 1
< 0.1%
0.2305010157 1
< 0.1%
0.2357853074 1
< 0.1%
0.2362990456 1
< 0.1%
0.2387447791 1
< 0.1%
0.2408129665 1
< 0.1%
0.2453677821 1
< 0.1%
ValueCountFrequency (%)
1 12506
41.7%
0.9999930609 1
 
< 0.1%
0.999988618 1
 
< 0.1%
0.9999826956 1
 
< 0.1%
0.9999795349 1
 
< 0.1%
0.9999323883 1
 
< 0.1%
0.9999266415 1
 
< 0.1%
0.9998992563 1
 
< 0.1%
0.9998632315 1
 
< 0.1%
0.9998454321 1
 
< 0.1%

gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size234.5 KiB
1
24000 
0
6000 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters30000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Length

2024-10-10T14:47:34.768666image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-10T14:47:34.945605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Most occurring characters

ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 24000
80.0%
0 6000
 
20.0%

Interactions

2024-10-10T14:47:23.747551image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:26.883809image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.140605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:33.433143image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:36.550483image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:39.860296image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:42.772757image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:45.986743image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.179048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.154598image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.339344image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:58.415157image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:01.715717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:04.783084image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.017778image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.085214image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.286082image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.498598image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:20.696272image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:23.913944image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.108404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.300537image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:33.608024image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:36.717717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.026578image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.093467image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.144774image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.337504image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.307513image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.505623image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:58.573777image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:01.882226image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:04.958379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.175656image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.257214image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.452564image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.661657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:20.874977image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:24.080435image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.298503image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.465875image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:33.791226image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:36.884265image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.185713image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.258482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.319988image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.504614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.480417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.663726image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:58.748101image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:02.049834image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:05.116469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.351464image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.419136image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.620173image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.814584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:21.029793image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:24.238155image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.473999image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.632818image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:33.966512image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:37.050855image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.335130image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.416203image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.478897image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.654668image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.638776image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.830986image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:58.977921image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:02.215972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:05.277505image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.515752image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.584709image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.786615image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.994487image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:21.196276image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:24.397496image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.648695image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.799451image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:34.133074image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:37.300604image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.487302image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.569469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.637481image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.821387image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.804725image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.979923image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:59.148486image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:02.382765image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:05.442482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.682199image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.743683image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.952903image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:18.153536image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:21.354669image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:24.555104image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.806298image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:30.952306image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:34.283828image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:37.616944image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.635557image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.719444image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.787316image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.971326image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:52.955877image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:56.147519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:59.307123image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:02.532579image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:05.591876image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.834702image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:11.902189image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:15.102686image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:18.303436image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:21.512735image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:24.893966image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:27.967857image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:31.123946image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:34.450413image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:37.768345image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:40.793282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:43.877009image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:46.953729image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:50.129362image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:53.113635image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:56.306280image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:59.457259image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:02.691391image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:05.750042image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:08.993395image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:12.060382image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:15.268926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:18.461556image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:21.671254image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:25.055416image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:28.214428image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:31.290618image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:34.616826image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:37.934926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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2024-10-10T14:47:10.760951image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:13.968740image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.163880image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:20.387922image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:23.438872image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:26.797769image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:29.983103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:33.252877image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:36.391920image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:39.710554image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:42.643955image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:45.822924image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:49.020959image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:51.995467image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:55.182431image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:46:58.256746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:01.557315image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:04.624816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:07.859360image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:10.927061image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:14.127188image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:17.328617image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:20.546335image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2024-10-10T14:47:23.596465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2024-10-10T14:47:35.101824image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
cent_fentropy_tgenderkurt_fkurt_tmean_fmean_tmed_fmed_tmin_fq25_fq25_tq75_fq75_tsfm_fskew_fskew_tstd_fstd_tzeroxrate_t
cent_f1.0000.0440.049-0.2420.0150.0820.1490.2080.1490.051-0.090-0.0230.0970.112-0.293-0.288-0.1320.0150.1410.033
entropy_t0.0441.0000.1780.125-0.113-0.5220.066-0.5620.067-0.6940.003-0.162-0.0380.699-0.060-0.0480.012-0.4560.3200.062
gender0.0490.1781.0000.2020.0410.1650.2800.1130.2820.1160.1190.0600.0040.1430.0990.1100.1220.1280.3440.029
kurt_f-0.2420.1250.2021.000-0.104-0.6600.255-0.7460.256-0.4250.4980.084-0.076-0.0510.8870.899-0.058-0.4620.307-0.040
kurt_t0.015-0.1130.041-0.1041.0000.1550.0040.1550.0040.173-0.0370.0300.270-0.116-0.0040.018-0.0290.151-0.094-0.021
mean_f0.082-0.5220.165-0.6600.1551.000-0.1300.927-0.1310.920-0.385-0.0050.071-0.321-0.381-0.4000.0150.919-0.321-0.008
mean_t0.1490.0660.2800.2550.004-0.1301.000-0.0541.0000.0580.3150.1930.0070.1290.2970.295-0.683-0.1050.9390.007
med_f0.208-0.5620.113-0.7460.1550.927-0.0541.000-0.0550.882-0.3140.0050.074-0.322-0.535-0.551-0.0640.782-0.2680.008
med_t0.1490.0670.2820.2560.004-0.1311.000-0.0551.0000.0570.3160.1930.0080.1290.2970.295-0.682-0.1060.9390.007
min_f0.051-0.6940.116-0.4250.1730.9200.0580.8820.0571.000-0.1630.0750.069-0.475-0.122-0.142-0.1040.882-0.200-0.029
q25_f-0.0900.0030.1190.498-0.037-0.3850.315-0.3140.316-0.1631.0000.048-0.037-0.0870.4520.460-0.118-0.1970.3260.004
q25_t-0.023-0.1620.0600.0840.030-0.0050.1930.0050.1930.0750.0481.0000.008-0.2260.1270.124-0.239-0.0160.141-0.089
q75_f0.097-0.0380.004-0.0760.2700.0710.0070.0740.0080.069-0.0370.0081.000-0.035-0.0500.009-0.0130.070-0.0280.005
q75_t0.1120.6990.143-0.051-0.116-0.3210.129-0.3220.129-0.475-0.087-0.226-0.0351.000-0.175-0.172-0.140-0.3440.3060.129
sfm_f-0.293-0.0600.0990.887-0.004-0.3810.297-0.5350.297-0.1220.4520.127-0.050-0.1751.0000.996-0.098-0.1560.276-0.061
skew_f-0.288-0.0480.1100.8990.018-0.4000.295-0.5510.295-0.1420.4600.1240.009-0.1720.9961.000-0.094-0.1740.277-0.059
skew_t-0.1320.0120.122-0.058-0.0290.015-0.683-0.064-0.682-0.104-0.118-0.239-0.013-0.140-0.098-0.0941.0000.071-0.5990.010
std_f0.015-0.4560.128-0.4620.1510.919-0.1050.782-0.1060.882-0.197-0.0160.070-0.344-0.156-0.1740.0711.000-0.256-0.019
std_t0.1410.3200.3440.307-0.094-0.3210.939-0.2680.939-0.2000.3260.141-0.0280.3060.2760.277-0.599-0.2561.0000.022
zeroxrate_t0.0330.0620.029-0.040-0.021-0.0080.0070.0080.007-0.0290.004-0.0890.0050.129-0.061-0.0590.010-0.0190.0221.000

Missing values

2024-10-10T14:47:27.011067image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-10T14:47:27.269908image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

mean_fstd_fmed_fmin_fq25_fq75_fskew_fkurt_fsfm_fcent_fmean_tstd_tmed_tq25_tq75_tskew_tkurt_tzeroxrate_tentropy_tgender
00.0300080.0794190.0138140.0051280.4369871.00.3509740.3776730.3473181.00.5475400.6436230.5479550.01.0000000.01.00.0000001.0000001
10.0395800.0934970.0159240.0070630.4749301.00.3908260.4186130.3863381.00.5788190.6660550.5793710.01.0000000.01.00.0000001.0000001
20.0499640.1129780.0223790.0089110.4277581.00.3679080.3775260.3659641.00.5449230.6226110.5452120.00.9188070.01.00.0000000.8610181
30.0678860.1261970.0321450.0107700.4018161.00.2982730.3041560.2968861.00.5026090.5723710.5028520.00.2980640.01.00.0000000.9723931
40.0658230.1298280.0272000.0098910.4046451.00.3168310.3231970.3149531.00.5506550.6347630.5507350.00.7409610.01.00.0034180.8644911
50.0412420.0946640.0170840.0064180.5076581.00.3426680.3611530.3393131.00.5795510.6771220.5803970.01.0000000.01.00.0000001.0000001
60.0388670.0880270.0170390.0062950.4450321.00.3428750.3621370.3394811.00.5544270.6430630.5546210.01.0000000.01.00.0107420.9706961
70.0433180.0813650.0260440.0077130.4317861.00.2875240.3065790.2852151.00.5274320.5906400.5277400.00.7710810.01.00.0000000.7569881
80.0620920.1187890.0275980.0092540.3921591.00.3098650.3163730.3083431.00.5041890.5791190.5044890.00.7053050.01.00.0014411.0000001
90.0334060.0852640.0145140.0055820.4715771.00.3575510.3886920.3530851.00.5438470.6368500.5440420.01.0000000.01.00.0000001.0000001
mean_fstd_fmed_fmin_fq25_fq75_fskew_fkurt_fsfm_fcent_fmean_tstd_tmed_tq25_tq75_tskew_tkurt_tzeroxrate_tentropy_tgender
299900.0126470.0397710.0053350.0022920.4103851.00.4158910.7632480.3978061.00.6337390.7578180.6346340.01.00.01.00.0062721.00
299910.0200370.0657830.0085410.0033170.4519421.00.3783060.4767230.3684141.00.5795710.7074930.5802870.01.00.01.00.0349041.00
299920.0157070.0608020.0064250.0028660.4648391.00.4356320.5973120.4219771.00.5739440.7097740.5743860.01.00.01.00.0090151.00
299930.0194520.0553190.0090280.0029190.4059941.00.3150510.4514230.3036121.00.5901600.7170030.5909810.01.00.01.00.0000001.00
299940.0150530.0472660.0067280.0027110.4269121.00.3937340.6051640.3797381.00.6359560.7614060.6367070.01.00.01.00.0000001.00
299950.0164940.0513960.0073090.0030820.4858061.00.3954890.5451690.3843571.00.6341170.7547700.6348020.01.00.01.00.0000001.00
299960.0190740.0650360.0075910.0036250.4754241.00.4592570.5449910.4506031.00.6199920.7420370.6205660.01.00.01.00.0000001.00
299970.0213460.0772630.0082400.0037210.4926091.00.4295510.5116160.4197131.00.5285910.6527280.5292660.01.00.01.00.0164671.00
299980.0124080.0504010.0052470.0024760.5040111.00.4542440.6454450.4408231.00.5852390.7177020.5859310.01.00.01.00.0000001.00
299990.0244780.0678190.0111580.0037530.3752211.00.3303410.4128530.3217411.00.6188620.7440220.6195900.01.00.01.00.0000001.00